515 related articles for article (PubMed ID: 32043519)
1. Bioinformatics analysis of prognostic significance of COL10A1 in breast cancer.
Zhang M; Chen H; Wang M; Bai F; Wu K
Biosci Rep; 2020 Feb; 40(2):. PubMed ID: 32043519
[TBL] [Abstract][Full Text] [Related]
2. Identification of prognostic significance of BIRC5 in breast cancer using integrative bioinformatics analysis.
Dai JB; Zhu B; Lin WJ; Gao HY; Dai H; Zheng L; Shi WH; Chen WX
Biosci Rep; 2020 Feb; 40(2):. PubMed ID: 32043523
[TBL] [Abstract][Full Text] [Related]
3. Bioinformatics analysis revealing prognostic significance of
Chen WX; Yang LG; Xu LY; Cheng L; Qian Q; Sun L; Zhu YL
Biosci Rep; 2019 Apr; 39(4):. PubMed ID: 30898978
[No Abstract] [Full Text] [Related]
4. Bioinformatics analysis of prognostic value of
Chen WX; Cheng L; Xu LY; Qian Q; Zhu YL
Biosci Rep; 2019 Mar; 39(3):. PubMed ID: 30837324
[No Abstract] [Full Text] [Related]
5. Cell division cycle proteinising prognostic biomarker of breast cancer.
Cheng L; Huang YZ; Chen WX; Shi L; Li Z; Zhang X; Dai XY; Wei JF; Ding Q
Biosci Rep; 2020 May; 40(5):. PubMed ID: 32285914
[TBL] [Abstract][Full Text] [Related]
6. Bioinformatics analysis of prognostic value of PITX1 gene in breast cancer.
Wang Q; Zhao S; Gan L; Zhuang Z
Biosci Rep; 2020 Sep; 40(9):. PubMed ID: 32830857
[TBL] [Abstract][Full Text] [Related]
7. Analysis of Collagen type X alpha 1 (COL10A1) expression and prognostic significance in gastric cancer based on bioinformatics.
Chen S; Wei Y; Liu H; Gong Y; Zhou Y; Yang H; Tang L
Bioengineered; 2021 Dec; 12(1):127-137. PubMed ID: 33371777
[TBL] [Abstract][Full Text] [Related]
8. Mining Prognostic Significance of MEG3 in Human Breast Cancer Using Bioinformatics Analysis.
Cui X; Yi Q; Jing X; Huang Y; Tian J; Long C; Xiang Z; Liu J; Zhang C; Tan B; Li Y; Zhu J
Cell Physiol Biochem; 2018; 50(1):41-51. PubMed ID: 30278461
[TBL] [Abstract][Full Text] [Related]
9. Expression Pattern and Prognostic Value of EPHA/EFNA in Breast Cancer by Bioinformatics Analysis: Revealing Its Importance in Chemotherapy.
Liang Z; Wang X; Dong K; Li X; Qin C; Zhou H
Biomed Res Int; 2021; 2021():5575704. PubMed ID: 33977106
[TBL] [Abstract][Full Text] [Related]
10. Bioinformatic analysis of the expression and prognostic value of chromobox family proteins in human breast cancer.
Li X; Gou J; Li H; Yang X
Sci Rep; 2020 Oct; 10(1):17739. PubMed ID: 33082469
[TBL] [Abstract][Full Text] [Related]
11. CD24 is a Potential Biomarker for Prognosis in Human Breast Carcinoma.
Jing X; Cui X; Liang H; Hao C; Yang Z; Li X; Yang X; Han C
Cell Physiol Biochem; 2018; 48(1):111-119. PubMed ID: 30001552
[TBL] [Abstract][Full Text] [Related]
12. Bioinformatics analysis of potential prognostic biomarkers among Krüppel-like transcription Factors (KLFs) in breast cancer.
Cheng L; Shi L; Dai H
Cancer Biomark; 2019; 26(4):411-420. PubMed ID: 31640084
[TBL] [Abstract][Full Text] [Related]
13. Bioinformatics analysis revealing prognostic significance of TIMP2 gene in breast cancer.
Chen WQ; Yang SJ; Xu WX; Deng F; Wang DD; Tang JH
Medicine (Baltimore); 2021 Oct; 100(42):e27489. PubMed ID: 34678879
[TBL] [Abstract][Full Text] [Related]
14. Overexpression of MUC1 predicts poor prognosis in patients with breast cancer.
Jing X; Liang H; Hao C; Yang X; Cui X
Oncol Rep; 2019 Feb; 41(2):801-810. PubMed ID: 30483806
[TBL] [Abstract][Full Text] [Related]
15. The expression and clinical significance of secretory leukocyte proteinase inhibitor (SLPI) in mammary carcinoma using bioinformatics analysis.
Xie W; Zhang H; Qin S; Zhang J; Fan X; Yin Y; Liang R; Long H; Yi W; Fu D; Ma C; Lv M; Yu F
Gene; 2019 Dec; 720():144088. PubMed ID: 31476404
[TBL] [Abstract][Full Text] [Related]
16. Keratin 17 is overexpressed and predicts poor survival in estrogen receptor-negative/human epidermal growth factor receptor-2-negative breast cancer.
Merkin RD; Vanner EA; Romeiser JL; Shroyer ALW; Escobar-Hoyos LF; Li J; Powers RS; Burke S; Shroyer KR
Hum Pathol; 2017 Apr; 62():23-32. PubMed ID: 27816721
[TBL] [Abstract][Full Text] [Related]
17. PPFIA1 is upregulated in liver metastasis of breast cancer and is a potential poor prognostic indicator of metastatic relapse.
Yang J; Wu NN; Huang DJ; Luo YC; Huang JZ; He HY; Lu HL; Song WL
Tumour Biol; 2017 Jul; 39(7):1010428317713492. PubMed ID: 28720060
[TBL] [Abstract][Full Text] [Related]
18. Identification of differentially expressed genes between triple and non-triple-negative breast cancer using bioinformatics analysis.
Zhai Q; Li H; Sun L; Yuan Y; Wang X
Breast Cancer; 2019 Nov; 26(6):784-791. PubMed ID: 31197620
[TBL] [Abstract][Full Text] [Related]
19. Age related influence of triple receptor status on metastatic breast cancer post relapse survival.
Todorovic-Rakovic N; Neskovic-Konstantinovic Z
J BUON; 2013; 18(4):851-8. PubMed ID: 24344008
[TBL] [Abstract][Full Text] [Related]
20. Bioinformatics identification of CCL8/21 as potential prognostic biomarkers in breast cancer microenvironment.
Chen B; Zhang S; Li Q; Wu S; He H; Huang J
Biosci Rep; 2020 Nov; 40(11):. PubMed ID: 33146700
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
